Mathematics & Optimization

Meta-learning Control Variates: Variance Reduction with Limited Data UAI 2023 Meta Optimal Transport ICML 2023 Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optimization ICML 2023 Meta-Sketch: A Neural Data Structure for Estimating Item Frequencies of Data Streams AAAI 2023 Metric Nearness Made Practical AAAI 2023 Metrizing Weak Convergence with Maximum Mean Discrepancies JMLR 2023 MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods ICML 2023 Microcanonical Hamiltonian Monte Carlo JMLR 2023 MIM4DD: Mutual Information Maximization for Dataset Distillation NeurIPS 2023 Mind the Gap: Offline Policy Optimization for Imperfect Rewards ICLR 2023 Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints ICML 2023 Minimal Solutions to Uncalibrated Two-view Geometry with Known Epipoles ICCV 2023 Minimax estimation of discontinuous optimal transport maps: The semi-discrete case ICML 2023 Minimax Instrumental Variable Regression and L_2 Convergence Guarantees without Identification or Closedness COLT 2023 Minimax Nonparametric Two-Sample Test under Adversarial Losses AISTATS 2023 Minimax-Optimal Location Estimation NeurIPS 2023 Minimax Optimal Rate for Parameter Estimation in Multivariate Deviated Models NeurIPS 2023 Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy NeurIPS 2023 Minimizing Dynamic Regret on Geodesic Metric Spaces COLT 2023 Minimizing Reachability Times on Temporal Graphs via Shifting Labels IJCAI 2023 Minimum-Entropy Coupling Approximation Guarantees Beyond the Majorization Barrier AISTATS 2023 Min-Max Submodular Ranking for Multiple Agents AAAI 2023 Mirror Sinkhorn: Fast Online Optimization on Transport Polytopes ICML 2023 Misspecification in Inverse Reinforcement Learning AAAI 2023 Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach ICLR 2023